Aashish Yadavally

Affiliations. Research. Academic Service. Contacts.

prof_pic.jpg

ECSS 4.417

The University of Texas at Dallas

Richardson, TX 75082

For starters, my first name is pronounced / ɑ:ʃi:ʃ /.

I am a fourth-year Ph.D. student in Computer Science at the University of Texas at Dallas. With Dr. Tien N. Nguyen as my research advisor, I am curently exploring problems at the intersection of Artificial Intelligence and Software Engineering, specifically to enable analysis of partial programs for improving security of software systems.

Through my academic journey, I have been fortunate to work under the guidance of/with wonderful people and researchers in:
  Dr. David Shaohua Wang is an Assistant Professor in the Department of Informatics, New Jersey Institute of Technology.
  Dr. Frederick Maier is the Associate Director of the Institute for Artificial Intelligence, University of Georgia.
  Dr. Hemant Patil heads the Speech Research Lab, and is a Professor at the Dhirubhai Ambani Institute for Information and Communication Technology (DA-IICT).

You may see me at the following Conferences or Events
  2023   ESEC/FSE (San Francisco, CA, USA), ICSE (Melbourne, Australia)
  2022   ASE (Detroit, MI, USA), ICSE (Pittsburgh, PA, USA), SANER (Virtual)

Favourite Quotes

  • “The future depends on what we do in the present.” ~ Mohandas Karamchand Gandhi
  • “If you work with determination and with perfection, success will follow.” ~ Dhirubhai Ambani

news

Feb 21, 2024 One paper accepted at FORGE 2024.
Jan 22, 2024 One paper accepted at FSE 2024.
Jan 15, 2024 Invited talk at TOOS, University of Luxembourg.
Dec 23, 2023 Two papers accepted at OOPSLA 2024.
Dec 1, 2023 Will be attending ESEC/FSE 2023 at San Francisco, USA.
Dec 1, 2023 Awarded the NSF Student Travel Grant to attend MAPS Workshop, co-located with ESEC/FSE 2023.
Oct 1, 2023 Will be serving in the Junior Program Committee at MSR 2024 in the Technical Research track.

selected publications

  1. FSE
    Predictive Program Slicing via Execution Knowledge-Guided Dynamic Dependence Learning
    Aashish Yadavally, Yi Li, and Tien N. Nguyen
    Proc. ACM Soft. Engg., 2024
  2. OOPSLA
    A Learning-Based Approach to Static Program Slicing
    Aashish Yadavally, Yi Li, Shaohua Wang, and Tien N. Nguyen
    Proc. ACM Program. Lang., 2024
  3. ESEC/FSE
    Commit-Level, Neural Vulnerability Detection and Assessment
    Yi Li, Aashish Yadavally, Jiaxing Zhang, Shaohua Wang, and Tien N. Nguyen
    In ESEC/SIGSOFT FSE, 2023
  4. ICSE
    (Partial) Program Dependence Learning
    Aashish Yadavally, Tien N. Nguyen, Wenbo Wang, and Shaohua Wang
    In ICSE, 2023

    🏆 Nominated for ACM SIGSOFT Distinguished Paper Award

  5. DeepVD: Toward Class-Separation Features for Neural Network Vulnerability Detection
    Wenbo Wang, Tien N. Nguyen, Shaohua Wang, Yi Li, Jiyuan Zhang, and Aashish Yadavally
    In ICSE, 2023
  6. SANER
    Phrase2Set: Phrase-to-Set Machine Translation and Its Software Engineering Applications
    Thanh V. Nguyen, Aashish Yadavally, and Tien N. Nguyen
    In SANER, 2022

    🏆 IEEE TCSE Distinguished Paper Award